Abstract P4-02-22: Breast microcalcification chemistry predicts DCIS prognosis
Authors: Jayakrupakar Nallala, Doriana Calabrese, Sarah Gosling, Esther Lips, Rachel Factor, Allison Hall, Sarah E. Pinder, Ihssane Bouybayoune, Lorraine King, Jeffrey Marks, Thomas Lynch, Donna Pinto, Jelle Wesseling, E Shelley Hwang, Keith Rogers, Nick Stone
Journal: Cancer Research (2023)

Abstract Introduction: Microcalcifications are a common feature in mammographic detection of ductal carcinoma in situ (DCIS), and occur in &amp;gt;80% of cases. Known to be present as type I (calcium oxalate-CaO) and type II (carbonated calcium hydroxyapatite-CHAP) microcalcifications, their association with DCIS and their role in the progression of DCIS to invasive breast cancer (IBC) remains unexplored. In an effort to understand the factors involved in DCIS prognosis, it is hypothesized that changes in the chemical composition of calcifications, in tandem with molecular changes in the surrounding soft tissue, will define patients with DCIS who will progress to develop IBC from those who remain with a stable DCIS phenotype. To this end, a novel label-free approach of hyperspectral imaging using mid-infrared (mid-IR) and Raman spectroscopy was used to probe calcification chemistry and molecular composition of the surrounding ductal and stromal soft tissue. The main aim of the work is to identify biomarkers for DCIS prognosis, based on chemical and molecular compositional changes of calcifications and the surrounding soft tissue. It is anticipated that the spectral biomarkers will provide patients and clinicians an informed risk assessment whether to undertake treatment for DCIS or to be placed under active surveillance. Methods: Tissue samples from 422 patient have been obtained and include (i) ‘pure DCIS’ (DCIS without recurrence) (n=193), (ii) ‘DCIS with invasive recurrence’ (DCIS from patients who subsequently were known to develop invasive disease) (n=123), (iii) ‘DCIS plus contemporaneous invasive cancer’ (n=44) and ‘benign’ (n=62) samples. Serial tissue sections were measured using mid-IR and Raman hyperspectral imaging approaches targeting the same calcification and soft tissue regions from specific DCIS ducts. Hyperspectral imaging data was initially pre-processed to digitally remove paraffin and unintended spectral interferences. The pre-processed data was subjected to cluster analysis followed by unsupervised and supervised machine learning classification models to identify spectral features associated with DCIS and its progression to IBC. Results: Cluster analysis based segmentation of hyperspectral images revealed histopathological features including calcifications, epithelium, necrotic areas, connective tissue and stroma. Spectra were extracted from each of the histopathological features using image coordinates, and biomodelling analysis was performed. Initial analysis of 314 calcification images from 170 patients with (i) ‘pure DCIS’ (n=118) and (ii) ‘DCIS with invasive recurrence’ (n=52) showed an area under the receiver operating characteristic (AUROC) mean value of 85% in distinguishing pure DCIS from DCIS that later recurred as IBC. The calcification features appeared to indicate pathology specific changes in phosphate and carbonate content as well as changes in magnesium whitlockite content. Similar analysis of the surrounding soft tissue spectral features showed an AUROC mean value of 85% (necrotic regions surrounding calcifications) and 76% (epithelium) respectively. The epithelial features showed changes in protein secondary structure and content, which together with the calcification changes indicate structural remodelling in DCIS that progresses to IBC, from those that do not. Perspectives: In the ongoing analyses of imaging data from 422 patients, it is anticipated that molecular/structural features from calcification and soft tissue imaging data will provide important cues in understanding DCIS prognosis and could be a promising way forward in determining management of DCIS risk and treatment underpinned by the identification of specific discriminatory spectral markers. Acknowledgments: This work was supported by Cancer Research UK and by KWF Kankerbestrijding (ref. C38317/A24043). Citation Format: Jayakrupakar Nallala, Doriana Calabrese, Sarah Gosling, Esther Lips, Rachel Factor, Allison Hall, Sarah E. Pinder, Ihssane Bouybayoune, Lorraine King, Jeffrey Marks, Thomas Lynch, Donna Pinto, Jelle Wesseling, E Shelley Hwang, Keith Rogers, Nick Stone. Breast microcalcification chemistry predicts DCIS prognosis [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P4-02-22.